Pedestrian Detection: An Evaluation of the State of the Art
Pedestrian Detection: An Evaluation of the State of the Art
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DOI：
10.1109/tpami.2011.155
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发表时间：
2012-04-01
影响因子：
23.6
通讯作者：
Perona, Pietro
中科院分区：
文献类型：
--
作者：
Dollar, Piotr;Wojek, Christian;Perona, Pietro
行人检测是计算机视觉中的关键问题，有几种应用具有积极影响生活质量的可能性。近年来，在单眼图像中检测行人的方法数量稳步增长。但是，使用了多个数据集和广泛不同的评估协议，使直接比较变得困难。为了解决这些缺点，我们在统一框架中对艺术状态进行了广泛的评估。我们做出了三个主要贡献：1）我们将一个大型，通知且现实的单眼探测数据集并研究了行人在城市场景中的大小，位置和闭塞模式的统计数据，2）我们提出了一种精致的人均评估方法，使我们能够进行六次探测和信息绩效，包括我们在验证和信息方面进行评估，并在范围内进行了评估和信息，并在范围内进行了评估，并在范围内进行了衡量的绩效，并实现了相关性的效果，并实现了关系的绩效，并实现了范围的关系。在六个数据集中验证了最先进的探测器。我们的研究使我们能够评估最新技术的状态，并为衡量未来的努力提供了一个框架。我们的实验表明，尽管取得了重大进展，但性能仍然有很大的改进空间。特别是，对于低分辨率和部分遮障的行人，发现令人失望。
Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to detecting pedestrians in monocular images has grown steadily. However, multiple data sets and widely varying evaluation protocols are used, making direct comparisons difficult. To address these shortcomings, we perform an extensive evaluation of the state of the art in a unified framework. We make three primary contributions: 1) We put together a large, well-annotated, and realistic monocular pedestrian detection data set and study the statistics of the size, position, and occlusion patterns of pedestrians in urban scenes, 2) we propose a refined per-frame evaluation methodology that allows us to carry out probing and informative comparisons, including measuring performance in relation to scale and occlusion, and 3) we evaluate the performance of sixteen pretrained state-of-the-art detectors across six data sets. Our study allows us to assess the state of the art and provides a framework for gauging future efforts. Our experiments show that despite significant progress, performance still has much room for improvement. In particular, detection is disappointing at low resolutions and for partially occluded pedestrians.